Description
In this role, you will design and build the data infrastructure that powers our next generation of Health and Fitness features — from ingesting raw sensor data to the platforms and tools that turn it into research insight. This includes architecting scalable data pipelines, ensuring user study data quality, gathering algorithm performance insights, and validating the software implementation. Key responsibilities of this role are: Design and develop scalable, parallelized data pipelines to process and transform complex, time-series health data captured from consumer-grade sensors Build tools and dashboards to visualize data and support data exploration, analysis, and research insights. Collaborate with study stakeholders to gather requirements and contribute to the study design, tooling development, and data quality monitoring processes. Design and run analytics to validate algorithm simulation output against ground truth, and build automated QA metrics to track feature performance over time Work closely with cross-functional teams including Software, Algorithms, and EPM to support design, integration, testing, and deployment of the health software.
Minimum Qualifications
BS degree in Computer Science, Engineering, Data Science, or a related technical field. Minimum of 3 years of industry experience building and maintaining large-scale data processing or simulation pipelines, or performing large-scale data analysis. Strong programming skills in Python, with a focus on writing clean, maintainable, and high-performance code. Familiarity with SQL for querying, transforming, and analyzing structured data. Hands-on experience with distributed computing frameworks such as Apache Spark. Comfort leveraging AI tools to accelerate problem-solving and development.
Preferred Qualifications
Applied machine learning experience, including building models on large datasets Experience working with sensor data, time-series data, or healthcare datasets Experience in cloud environments (AWS, GCP, or Azure) with containerization tools like Docker and Kubernetes Comfort working in Linux environments, including scripting, navigation, and basic troubleshooting Exposure to clinical studies, FDA validation processes, or regulated health environments Experience building iOS apps; familiarity with C++ is a plus Self-directed and self-motivated, with experience producing architecture and design documents Strong communication and cross-functional collaboration skills, including translating requirements from technical and non-technical partners into practical engineering tasks
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